Dental Computer-aided Design Software Research Articles

A Finite Element Analysis Study of Edentulous Model with Complete Denture to Simulate Masticatory Movement.

The purposes of this study are to establish and validate a finite element (FE) model using finite element analysis methods and to identify optimal loading conditions to simulate masticatory movement. A three-dimensional FE model of the maxillary and mandibular cortical bone, cancellous bone, and gingiva was constructed based on edentulous cone-beam-computed tomography data. Dental computer-aided design software was used to design the denture base and artificial teeth to produce a complete denture. Mesh convergence was performed to derive the optimal mesh size, and validation was conducted through comparison with mechanical test results. The mandible was rotated step-by-step to induce movements similar to actual mastication. Results showed that there was less than a 6% difference between the mechanical test and the alveolar bone-complete denture. It opened 10° as set in the first stage, confirming that the mouth closed 7° in the second stage. Occlusal contact occurred between the upper and lower artificial teeth as the mouth closed the remaining angle of 3° in the third stage while activating the masseter muscle. These results indicate that the FE model and masticatory loading conditions developed in this study can be applied to analyze biomechanical effects according to the wearing of dentures with various design elements applied.

Impact of marginal defects on the accuracy of automated finish line detection in tooth preparation.

The present study aimed to evaluate the accuracy of automated detection of preparation finish lines in teeth with defective margins. An extracted first molar was prepared for a full veneer crown, and marginal defects were created and scanned (discontinuity of finish line: 0.5, 1.0, and 1.5 mm; additional line angle: connected, partially connected, and disconnected). Six virtual defect models were entered into CAD software and the preparation finish line was designated by 20 clinicians (CAD-experienced group: n = 10; CAD-inexperienced group: n = 10) using the automated finish line detection method. The accuracy of automatic detection was evaluated by calculating the 3D deviation of the registered finish line. The Kruskal-Wallis and Mann-Whitney U tests were used for between-group comparisons (α = 0.05). The deviation values of the registered finish lines were significantly different according to conditions with different amounts of finish line discontinuity (P < 0.001). There was no statistical difference in the deviation of the registered finish line between models with additional line angles around the margin. Moreover, no statistical difference was found in the results between CAD-experienced and CAD-inexperienced operators. The accuracy of automated finish line detection for tooth preparation can differ when the finish line is discontinuous. The presence of an additional line angle around the preparation margin and prior experience in dental CAD software do not affect the accuracy of automated finish line detection.

A novel dice-inspired multifunctional 3D printing guided splint for minimally invasive access cavity preparation and canal orifice identification.

The minimally invasive endodontics could retain more peri-cervical dentin (PCD) and other important dental structures, thus realizing the minimal loss of teeth structures and preserving the strength and function of the endodontically treated tooth (ETT). The search for abnormal root canals or calcified root canals could be quite time-consuming and increase the risk of perforation. This study introduced a novel multifunctional 3D printing guided splint inspired by the dice, which can achieve the minimally invasive access cavity preparation and canal orifice identification. Data were collected from an outpatient with dens invaginatus. Cone-beam Computed Tomography (CBCT) revealed a type III invagination. The CBCT data of the patient were imported into a computer-aided design (CAD) software (Exocad 3.0; Exocad GmbH) for the 3D reconstruction of jaw bones and teeth. The dice-inspired 3D printing guided splint consists of the sleeve and guided splint. The sleeve with minimal invasive opening channel and orifice locating channel were designed with a reverse-engineering software (Geomagic Wrap 2021). The reconstructed models in the Standard Template Library (STL) format were imported into a CAD software. The design of the template was aided by the dental CAD software in Splint Design Mode. The sleeve and splint were exported into the STL files separately. A 3D printer (ProJet® 3600 3D Systems) was used to separately generate the sleeve and guided splint, and was made by stereolithography and processed in a medical resin (VisiJet M3 StonePlast). The novel multifunctional 3D printing guided splint could be set in position. The opening side in the sleeve was selected and the sleeve was inserted in place. The minimal invasive opening was made in the crown of the tooth to access the pulp. The sleeve was draw out and turned to the orifice location side, and then inserted in place. The target orifice was located rapidly. This novel dice-inspired multifunctional 3D printing guided splint allow dental practitioners to gain accurate, conservative, and safe cavity access from teeth with anatomical malformations. Complex operations might be carried out with less reliance on the operator's experience than with conventional access preparations. This novel dice-inspired multifunctional 3D printing guided splint would have a broad application in the dental field.

Requirements for Dental CAD Software: A Survey of Korean Dental Personnel

This study aimed to evaluate the needs of dentists, dental technicians, dental hygienists, and dental-related workers in terms of dental computer-aided design (CAD) software and artificial intelligence (AI). Based on a factor analysis, 57 survey items were assigned to six categories: (a) considerations when purchasing dental CAD software; (b) prosthesis design process; (c) dental CAD function; (d) use of AI dental CAD crown and denture design; (e) impact of AI; and (f) improvements in AI features. Overall, 93 participants were included in the study, and the reliability of the resultant survey data was estimated using Cronbach’s alpha coefficient. Statistically significant factors in each category were identified using one-way analysis of variance and Tukey’s honestly significant difference test (α = 0.05). The results revealed that design quality, design convenience and reproducibility, margin line setting, and automatic margin setting were considered most important in their respective categories (p &lt; 0.05). There were also significant differences in the importance of certain items, such as branding importance and functional diversity, among different dental personnel groups (p &lt; 0.05). Design speed and convenience were also found to be more important to dentists and dental hygienists compared to other dental personnel (p &lt; 0.05). The importance of specific survey items varied significantly based on age, dental personnel, and work experience groups. Dental personnel, such as dentists and dental technicians, assigned greater importance to certain factors, such as branding, functional diversity, design speed, and compatibility with CAM equipment, compared to other occupational groups.

Reliability of automatic finish line detection for tooth preparation in dental computer-aided software.

This study aimed to investigate the accuracy of automatic tooth finish line registration compared to manual registration with regard to various finish line configurations and dental computer-aided design (CAD) software. Finish line registrations were performed on 15 digital tooth models with different finish line configurations (edge roundness radius = 0 mm, 0.2 mm, and 0.4 mm; edge angle = 30°, 60°, 90°, 120°, and 150°) using automatic and manual methods for designing virtual copings (N = 150). The discrepancies between the registered finish line extracted from the copings and the actual finish line segmented from the digitized tooth model were measured. Three-way analysis of variance (ANOVA) and post-hoc analyses with Bonferroni correction (α = 0.05) were used to analyze the results. The finish line configurations, registration methods, and CAD software interacted with the accuracy of the registered finish line (p = 0.001). The automatic finish line registration method exhibited larger error values than the manual method, especially at high finish line edge roundness and obtuse edge angles for both EXOCAD and R2CAD software (p < 0.001). The difference in dental CAD software affected the registration accuracy in the automatic method (p < 0.001), but not in the manual method (p = 0.676). Finish line registration errors may occur when the automatic registration method is applied to the indistinct edge of tooth preparation. The accuracy of the automatic finish line registration could differ according to the CAD software program.

Effect of computer literacy on the working time of the dental CAD software program.

The purpose of this study was to compare the correlation between the learning effect of dental computer-aided design (CAD) software and computer literacy in the clinical and preclinical experience groups of computer-aided design and computer-aided manufacturing (CAD/CAM). A total of 28 participants were recruited, including 14 dental students and 14 dental technicians. Their working time was evaluated using a custom abutment design with two dental CAD software program (exocad GmbH and Deltanine). The working time of custom abutment design was measured 3 times. A survey was conducted to evaluate the computer literacy. For statistical analysis, Mann-Whitney U test was used to analyze the difference between the clinical and preclinical experience groups and the correlation between computer literacy and reduction in working time was confirmed by Spearman's Rank correlation analysis (α=.05). The median working time showed the clinical experience group had faster than the preclinical experience group (P<.001). On the other hand, the reduction in working time was higher in the preclinical experience group (P=.002). Only preclinical experience group had a significant positive correlation between the computer literacy and reduction in working time (P<.001). Basic computer skills are required for first-time users to achie ve an excellent learning effect of dental CAD software program.

In vitro evaluation of the application of digital individual tooth tray in the impression making of mandibular full-arch crown abutments

Objective To establish a method for the production of digital individual tooth tray based on three-dimensional (3D) scan, computer-aided design (CAD) and 3D printing, and to evaluate the effect of impression taking of full-arch crown abutments by digital individual tooth tray technique and conventional method through in vitro study. Methods The full crown preparation was performed on all the fourteen resin teeth in a standard model of mandibular dentition. The surface data of prepared abutments was collected by 3D scanning. A new project was created in a dental CAD software including all the fourteen teeth in the mandibular dentition. The design modules of anatomy crown and coping were selected for each tooth. The dentition was divided for three sections: right posterior teeth, anterior teeth, and left posterior teeth areas. The connector design was added between the abutments within the same section. The scanned data of the abutments were imported. The occlusal plane and insertion path were determined. The position of margin line, as well as the shape of anatomy crown and connector as the main body of the individual tooth tray were designed for each abutment. The shape of coping was generated as the space for holding the impression material. The finalized data of the main body was imported into Geomagic software. The retentive attachment was added at the external surface and the tissue stop was formed at the internal surface. The completed individual tooth tray was manufactured by 3D printing with resin material. The data of full-arch crown abutments were modified and printed. The conventional dentition trays A and B, as well as digital individual tooth tray were designed and printed for four copies each. The polyether impressions of the full-arch abutments were made by conventional one-step method using dentition tray A, and by sectional-impression technique using digital individual tooth tray and dentition tray B for four times each. The time spent for each impression taking and the numbers of defects at the shoulder and axial/occlusal surface in each impression were recorded. The impression quality of each abutment was evaluated. The overall quality distribution and the pass rate of abutments between the two methods were analyzed. Results The impressions made by conventional method had more defects at shoulder than those made by digital individual tooth tray technique. No difference of the number of defects at axial/occlusal surface between the two methods was observed. The digital individual tooth tray technique for the full-arch abutment impression exhibited higher pass rate of abutments and better quality of impression, compared with conventional methods. Conclusion A new method for the production of digital individual tooth tray based on digital scanning, CAD and 3D printing was established. Compared with conventional method, using digital individual tooth tray technique for impression taking of full-arch abutments can achieve better effect.

Effect of varying levels of expertise on the reliability and reproducibility of the digital waxing of single crowns: A preliminary in vitro study

Statement of problemThe digital waxing of single crowns can be affected by the quality of intraoral scans and use of computer-aided design (CAD) software programs. However, clinical outcomes of the resulting crowns are also affected by computer-aided manufacturing (CAM) methodologies. Studies on the effect of different levels of expertise on digital waxing are lacking. PurposeThe purpose of this in vitro study was to assess the impact of different levels of expertise on the reliability and reproducibility of margin outlining during digital waxing. Material and methodsThirty analogs of implant stock abutments (Ø4.8×4 mm) were embedded into resin blocks. To simulate different clinical situations, abutments were divided into 3 groups: 10 abutments (group GOS) received artificial gingiva and were scanned with an open system intraoral scanner, while 10 abutments with (group GIS) and 10 abutments without artificial gingiva (group IS) were scanned with an intraoral scanner within an integrated CAD-CAM system. All resulting standard tessellation language (STL) files were used by 2 different observers (an experienced CAD professional and a clinician with basic CAD knowledge) to digitally design a left mandibular central incisor in the same software program. All resulting digital crown designs were exported to STL files to assess crown margin accuracy at the coupling interface by superimposition with the control STL file of the scan body designed for the same abutment by the manufacturer. For this purpose, a CAD software program was used to automatically calculate median, minimum, and maximum deviations of margins in millimeters. Statistically significant pairwise differences among groups and between observers were assessed with the Wilcoxon signed-rank test (α=.05). ResultsFor the CAD professional, median deviations between designed crown STL files and the control STL of the scan body were 0.08 mm (range: 0.04 to 0.15) for group GOS; 0.10 mm (range: 0.06 to 0.18) for group GIS; and 0.05 mm (range: 0.03 to 0.08) for group IS. For the clinician, median deviations were 0.08 mm (range: 0.04 to 0.12) for group GOS; 0.11 mm (range: 0.07 to 0.17) for group GIS; and 0.05 mm (range: 0.04 to 0.11) for group IS. There were no significant differences between observers (P>.05). However, statistically significant differences were found between group IS and the other 2 groups (P=.001) but not between groups GOS and GIS (P>.05). ConclusionsThe present findings suggest that a digital wax pattern made with a dental CAD software program is not affected by varying levels of expertise but might be affected by subgingival margins.

Prediction of learning curves of 2 dental CAD software programs, part 2: Differences in learning effects by type of dental personnel

Statement of problemDental computer-aided design (CAD) software programs are essential elements of the digital workflow. Therefore, it is necessary to study the learning effect of dental CAD software programs for efficient use. PurposeThe purpose of this in vitro study was to predict the learning curve of dental CAD software programs according to dental personnel by using the Wright model and to investigate the tendency of dental personnel to reduce working time according to repeated learning. Material and methodsA total of 36 participants were recruited, including an equal number of dentists, dental technicians, and dental students (12 each). A custom abutment design was evaluated by using exocad CAD and Deltanine CAD software programs. The design was carried out in the following order: 4 steps repeated 3 times each. This study applied the formula of the Wright model to predict 500 repetitive times. In the statistical analysis, 3-repetition and 500-repetition times were analyzed with the Kruskal-Wallis H test and Friedman test (α=.05), and a post hoc comparison was performed by using the Mann-Whitney U-test and Bonferroni correction method (α=.017). ResultsThree repetitions resulted in shorter working time in the dental technician group. The 3-repetition time decreased statistically for all dental personnel (P<.001). The time for 500 repetitions showed a statistically significant difference according to the type of dental personnel (P=.036), but no significant difference was found after the fourth iteration (fifth iteration: P=.076). Furthermore, the estimated time of 500 iterations decreased statistically significantly from the first to the 500th iteration (P<.001). ConclusionsAll dental personnel showed learning effects of dental CAD software programs. Although the dental technician group initially showed less working time, after initial learning, the same learning effect appeared, regardless of the type of dental personnel.

Prediction of the learning curves of 2 dental CAD software programs

Statement of problemDental clinical procedures are being replaced by digital workflows. Therefore, the time necessary to learn dental computer-aided design (CAD) software to achieve a change in the digital workflow should be evaluated. PurposeThe purpose of this study was to predict the learning curve according to the type of dental CAD software with the Wright model and to determine the rate of improvement in the learner’s working time with iterative learning. Material and methodsA total of 40 participants with various degrees of experience with dental computer-aided design and computer-aided manufacturing (CAD-CAM) systems were recruited. The 4 specified steps of a custom abutment design were performed with 3DSystem CAD software (Daesung) and exocad DentalCAD (exocad GmbH) software and were repeated 3 times in stages. The times were analyzed with repeated-measures 1-factor and 2-factor analyses. The learning time for 300 design iterations was estimated by applying the Wright model formula, and the 300-repetition times were analyzed with the Mann-Whitney U test (α=.05). Resultsexocad had a longer mean learning time than the 3DSystem. The overall change with repeated learning was significantly different (P<.001), and all differences were found in the first to third iterations. Software-dependent differences were also observed (P=.005). The Mann-Whitney U test also revealed a significant difference between the 2 software programs (P=.015), but no significant difference was found after the 56th iteration (57th iteration: P=.051). ConclusionsAs the time reduction patterns for iterative learning differ depending on the type of CAD software, the learning curves may differ according to the type of software. As the operator’s skill increased through iterative learning, the differences in learning times between the software programs gradually disappeared.